Method development for the quantification of nine nitazene analogs and brorphine in Dried Blood Spots utilizing liquid chromatography - tandem mass spectrometry

The detection of nitazenes in biological fluids is increasingly needed as they are repeatedly reported in intoxication and overdose cases. A simple method for the quantification of low levels of nine nitazene analogs and brorphine in Dried Blood Spots (DBS) was developed and validated. 10 μL of spiked whole blood is deposited on a Capitainer®B card and allowed to dry. The spot is punched out, and extracted with 500 μL methanol:acetonitrile (3:1 v/v) added with 1.5 μL of fentanyl-D5 as the internal standard. After stirring, sonication, and centrifugation of the vial, the solvent is dried under nitrogen, the extract is reconstituted in 30 μL methanol, and 1 μL is injected into a UHPLC-MS/MS instrument. The method validation showed linear calibration in the 1-50 ng/mL range, LOD values ranging between 0.3 ng/mL (isotonitazene) and 0.5 ng/mL (brorphine), average CV% and bias% within 15 % and 10 % for all compounds, respectively. The matrix effect due to blood and filter paper components was within 85-115 % while recovery was between 15-20 %. Stability tests against time and temperature showed no significant variations for storage periods up to 28 days. Room temperature proved to represent the best samples storage conditions. UHPLC-MS/MS proved capable to reliably identify all target analytes at low concentration even in small specimen volumes, as those obtained from DBS cards, which in turn confirmed to be effective and sustainable micro-sampling devices. This procedure improves the efficiency of toxicological testing and provides an innovative approach for the identification of the nitazene class of illicit compounds.

Enhancing breast cancer screening with urinary biomarkers and Random Forest supervised classification: A comprehensive investigation

OBJECTIVES

Urinary sex hormones are investigated as potential biomarkers for the early detection of breast cancer, aiming to evaluate their relevance and applicability, in combination with supervised machine-learning data analysis, toward the ultimate goal of extensive screening.

METHODS

Sex hormones were determined on urine samples collected from 250 post-menopausal women (65 healthy - 185 with breast cancer, recruited among the clinical patients of Candiolo Cancer Institute FPO-IRCCS (Torino, Italy). Two analytical procedures based on UHPLC-MS/HRMS were developed and comprehensively validated to quantify 20 free and conjugated sex hormones from urine samples. The quantitative data were processed by seven machine learning algorithms. The efficiency of the resulting models was compared.

RESULTS

Among the tested models aimed to relate urinary estrogen and androgen levels and the occurrence of breast cancer, Random Forest (RF) proved to underscore all the other supervised classification approaches, including Partial Least Squares - Discriminant Analysis (PLS-DA), in terms of effectiveness and robustness. The final optimized model built on only five biomarkers (testosterone-sulphate, alpha-estradiol, 4-methoxyestradiol, DHEA-sulphate, and epitestosterone-sulphate) achieved an approximate 98% diagnostic accuracy on replicated validation sets. To balance the less-represented population of healthy women, a Synthetic Minority Oversampling TEchnique (SMOTE) data oversampling approach was applied.

CONCLUSIONS

By means of tunable hyperparameters optimization, the RF algorithm showed great potential for early breast cancer detection, as it provides clear biomarkers ranking and their relative efficiency, allowing to ground the final diagnostic model on a restricted selection five steroid biomarkers only, as desirable for noninvasive tests with wide screening purposes.

A multivariable analysis delineating hair color, hair dyeing, and hat wearing as predictors of level of cocaine and MDMA detection in human hair samples

Research suggests that hair color, hair dyeing, and perspiration can bias hair test results regarding drug exposure, but research is needed to examine such associations in a multivariable manner. In this epidemiology study, adults were surveyed entering nightclubs and dance festivals in New York City, and 328 provided hair samples, which were analyzed using ultra-high-performance liquid chromatography-tandem mass spectrometry to determine the level of detection of cocaine and 3,4-methylenedioxymethamphetamine (MDMA). Reporting use was not an inclusion criterion for analysis. We used two-part multivariable models to delineate associations of hair color, past-year hair dyeing, and frequency of past-month hat wearing (which may increase perspiration) in relation to any vs. no detection of cocaine and MDMA as well as level of detection, controlling for hair length, self-reported past-year cocaine/ecstasy/MDMA use, and age, sex, and race/ethnicity. Those reporting having dyed their hair were at increased odds of having any level of cocaine detected (adjusted odds ratio [aOR] = 3.75, 95% CI confidence interval [CI]: 1.85-6.70), and compared to those with brown hair, those with blond(e) hair on average had lower levels of cocaine (ng/mg) detected (beta = -7.97, p = 0.025). Those reporting having dyed their hair were at increased odds of having any level of MDMA detected (aOR = 3.05, 95% CI: 1.44-6.48), and compared to those who reported never wearing a hat, those who reported wearing a hat daily or almost daily on average had lower levels of MDMA (ng/mg) detected (beta = -6.61, p = 0.025). This study demonstrates the importance of using multivariable models to delineate predictors of drug detection.

Detection of fentanyl, synthetic opioids, and ketamine in hair specimens from purposive samples of American and Italian populations

With the current crisis related to the diffusion of fentanyl and other novel opioids in several countries and populations, new and effective approaches are needed to better elucidate the phenomenon. In this context, hair testing offers a unique perspective in the investigation of drug consumption, producing useful information in terms of exposure to psychoactive substances. In this research, we applied targeted ultra-high performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) analytical methods to detect novel synthetic and prescription opioids and other common controlled psychoactive drugs in the keratin matrix. A total of 120 hair samples were analyzed from the United States (US) and Italy, segmented when longer than 6 cm, and then analyzed. In the 60 samples (83 segments in total) analyzed from a purposive sample of data collected in the US, fentanyl was detected in 14 cases (16.9%), with no detection of nitazens or brorphine. We also detected fentanyl metabolites, despropionyl-p-fluorofentanyl, and prescription opioids. In the 60 samples collected in Italy (91 segments in total), ketamine was the most prevalent compound detected (in 41 cases; 45.1%), with ketamine demonstrating a strong correlation with detection of amphetamines and MDMA, likely due to co-use of these substances in recreational contexts. Several common drugs were also detected but no exposure to fentanyl or its analogs were detected. Results of this retrospective exploration of drug use add to increasing evidence that hair testing can serve as a useful adjunct to epidemiology studies that seek to determine biologically confirmed use and exposure in high-risk populations.

Breaking with trends in forensic dating: A likelihood ratio-based comparison approach

Further steps toward understanding the time-related information contained within bloodstains found at the crime scene are rightly considered a top priority in forensic science. Contrary to widely held assumptions, the reason for the delayed exploitation of bloodstains dating methods in practice is not the lack of suitable analytical techniques for monitoring degradation processes. The problem lies in the variability of the environmental and circumstantial conditions, playing a vital role in the degradation kinetics of blood deposits. The present article demonstrates the possibility of breaking with current approaches based on absolute age estimations to finally answer time-centered questions in real forensic scenarios. The proposed novel framework for situating forensic traces in time is based on the likelihood ratio assessment of the (dis)similarity between the evidence decomposition and sets of reference materials obtained through supervised aging. In such a strategy, every dating procedure is constructed on a case-by-case basis to fit examined blood traces, thereby limiting the adverse influence of external factors on the validity of age estimations and providing a way for future crime scene implementation.

Wastewater surveillance of 105 pharmaceutical drugs and metabolites by means of ultra-high-performance liquid-chromatography-tandem high resolution mass spectrometry

Water pollution from pharmaceutical drugs is becoming an environmental issue of increasing concern, making water quality monitoring a crucial priority to safeguard public health. In particular, the presence of antidepressants, benzodiazepines, antiepileptics, and antipsychotics require specific attention as they are known to be harmful to aquatic biota. In this study, a multi-class comprehensive method for the detection of 105 pharmaceutical residues in small (30 mL) water samples was developed according to fit-for-purpose criteria and then applied to provide wide screening of samples obtained from four Wastewater Treatment Plants (WWTPs) in northern Italy. The filtered samples (0.22 µm filters) were extracted by SPE, and then eluted. 5 µL of the concentrated samples were analyzed by a UHPLC-QTOF-HRMS method validated for screening purposes. Adequate sensitivity was recorded for all target analytes, with limits of detection below 5 ng/L for 76 out of 105 analytes. A total of 23 out of the 105 targeted pharmaceutical drugs was detected in all samples. Several further compounds were detected over wide concentration intervals, ranging from ng/L to µg/L. In addition, the retrospective analysis of full-scan QTOF-HRMS data was exploited to carry out an untargeted screening of some drugs' metabolites. As a proof of concept, it was investigated the presence of the carbamazepine metabolites, which is among the most frequently detected contaminants of emerging concern in wastewater. Thanks to this approach, 10,11-dihydro-10-hydroxycarbamazepine, 10,11-dihydro-10,11-dihydroxycarbamazepine and carbamazepine-10,11-epoxide were identified, the latter requiring particular attention, since it exhibits antiepileptic properties similar to carbamazepine and potential neurotoxic effects in living organism.

Metabolic study of new psychoactive substance methoxpropamine in mice by UHPLC-QTOF-HRMS

Methoxpropamine (MXPr) is an arylcyclohexylamine dissociative drug structurally similar to 3-methoxyeticyclidine, ketamine, and deschloroketamine, recently appeared in the European illegal market, and was classified within the new psychoactive substances (NPS). Our study investigated the metabolism of MXPr to elucidate the distribution of the parent drug and its metabolites in body fluids and fur of 16 mice. After the intraperitoneal administration of MXPr (1, 3, and 10 mg/kg), urine samples from eight male and eight female mice were collected every hour for six consecutive hours and then at 12- to 24-h intervals. Additionally, plasma samples were collected 24 h after MXPr (1 and 3 mg/kg) administration. Urine and plasma were diluted 1:3 with acetonitrile/methanol (95:5) and directly injected into the UHPLC-QTOF-HRMS system. The phase-I and phase-II metabolites were preliminarily identified by means of the fragmentation patterns and the exact masses of both their precursor and fragment ions. Lastly, the mice fur was analyzed following an extraction procedure specific for the keratin matrix. Desmethyl-MXPr-glucoronide was identified in urine as the main metabolite, detected up to 24 h after administration. The presence of norMXPr in urine, plasma, and fur was also relevant, following a N-dealkylation process of the parent drug. Other metabolites that were identified in fur and plasma included desmethyl-MXPr and dihydro-MXPr. Knowledge of the MXPr metabolites evolution is likely to support their introduction as target compounds in NPS toxicological screening analysis on real samples, both to confirm intake and extend the detection window of the dissociative drug MXPr in the biological matrices.

GC-MS identification and quantification of the synthetic cannabinoid MDMB-4en-PINACA in cannabis-derived material seized in the Turin Metropolitan Area (Italy)

BACKGROUND

the presence of the synthetic cannabinoid receptor agonist MDMB-4en-PINACA in adulterated low-THC cannabis products was recently highlighted in several reports. Moreover, numerous intoxication cases involving MDMB-4en-PINACA have been described.

OBJECTIVE

In order to monitor the diffusion of cannabis products containing MDMB-4en-PINACA in our territory, a total of 358 cannabis-derived samples (213 vegetal material and 145 resins) seized in the period November 2020 - February 2021 in the western Piedmont Area (Italy) was analyzed.

METHODS

General screening analyses for traditional and synthetic cannabinoids were performed by a GC-MS device operating in full scan mode (40-600 amu). The MDMB-4en-PINACA was quantified by means of a specific GC-SIM-MS protocol purposely developed and validated, while the quantification of THC, CBD, and CBN was carried out by a GC-SIM-MS method routinely employed in our laboratory.

RESULTS

MDMB-4en-PINACA was detected in 12 out of 358 samples (3.4% of the total). Among these, the molecule was found in 11 vegetal materials and in one resin sample. Considering solely the analysis of the 213 herb products, a positive rate of 5.2% was found for the presence of MDMB-4en-PINACA in these samples. MDMB-4en-PINACA was found in the seized materials at concentration levels ranging from 0.4 up to 6.3 mg/g (mean 2.5 mg/g; median 1.7 mg/g). Concerning the traditional cannabinoids, the THC concentration was in the interval 3-43 mg/g (mean 12 mg/g; median 7 mg/g), while CBD was found at higher concentrations in all specimens, specifically in the range 47-140 mg/g (mean 87 mg/g; median 80 mg/g).

CONCLUSIONS

The adulteration of low-THC cannabis products with synthetic cannabinoid receptor agonists is a widespread phenomenon today. Since these substances are potentially more toxic than THC, their consumption poses a high risk of overdose for unaware users and a health-threatening situation. This study confirmed the sporadic presence on the market of CBD-prevalent cannabis products adulterated with MDMB-4en-PINACA.

Development and Validation of a GC-EI-MS/MS Method for Ethyl Glucuronide Quantification in Human Hair

Ethyl glucuronide (EtG) is a minor, non-oxidative ethanol metabolite detectable in several matrices for specific periods of time. In recent years, quantification of EtG in hair has been established as the most reliable biomarker for long-term alcohol consumption, with the Society of Hair Testing offering cut-off values for assessment of both abstinence and heavy drinking. Instrumental constrains and wide inter- and intra-laboratory variability represent the ultimate barriers to widespread acceptance of hair EtG determination in the forensic context. In this study, a new analytical method for hair EtG based on gas chromatographic (GC) separation, electron impact (EI) ionization, and tandem mass spectrometry (MS/MS) detection was developed and validated. At the same time, several parameters for sample pretreatment and instrumental analysis were optimized using real hair samples obtained from different drinking subjects. A full-factorial design-of-experiment approach included procedures for hair washing, pulverization, and extraction. Rigorous multi-step washing proved not to reduce the EtG content extracted in the subsequent sample incubation. Hair pulverization with a ball mill significantly improved the EtG extraction from the keratin matrix and allowed us to reduce the time needed for the subsequent extraction step, without affecting the extraction recovery. The hair extract was derivatized with N-methyl-N-(trimethylsilyl)-trifluoroacetamide. Upon electron impact ionization of the EtG-TMS derivative, triple quadrupole mass analyzers were operated in the selected reaction monitoring (SRM) mode using the fragment m/z 405 as the precursor ion (m/z 410 for the EtG-D5 internal standard), the transitions m/z 405 → 359 and m/z 410 → 359 for quantitation, and m/z 405 → 331 and m/z 405 → 287 for qualification/confirmation, all at 10 V collision energy. The final method was fully validated and then applied to 25 real hair samples. The calibration curve proved linear between 6 and 60 pg/mg. The limit of detection (LOD) was 4 pg/mg. Intra- and inter-assay precision and accuracy tests showed a variability and bias close to 15% or lower over the entire calibration range. The new method is routinely applied in the Italian State Police’s toxicology laboratory for hair analyses addressed to exclude excessive alcohol drinking and verify the psycho-physical requirements of the personnel.

Comprehensive biomarker profiles and chemometric filtering of urinary metabolomics for effective discrimination of prostate carcinoma from benign hyperplasia

Prostate cancer (PCa) is the most commonly diagnosed cancer in male individuals, principally affecting men over 50 years old, and is the leading cause of cancer-related deaths. Actually, the measurement of prostate-specific antigen level in blood is affected by limited sensitivity and specificity and cannot discriminate PCa from benign prostatic hyperplasia patients (BPH). In the present paper, 20 urine samples from BPH patients and 20 from PCa patients were investigated to develop a metabolomics strategy useful to distinguish malignancy from benign hyperplasia. A UHPLC-HRMS untargeted approach was carried out to generate two large sets of candidate biomarkers. After mass spectrometric analysis, an innovative chemometric data treatment was employed involving PLS-DA classification with repeated double cross-validation and permutation test to provide a rigorously validated PLS-DA model. Simultaneously, this chemometric approach filtered out the most effective biomarkers and optimized their relative weights to yield the highest classification efficiency. An unprecedented portfolio of prostate carcinoma biomarkers was tentatively identified including 22 and 47 alleged candidates from positive and negative ion electrospray (ESI+ and ESI-) datasets. The PLS-DA model based on the 22 ESI+ biomarkers provided a sensitivity of 95 ± 1% and a specificity of 83 ± 3%, while that from the 47 ESI- biomarkers yielded an 88 ± 3% sensitivity and a 91 ± 2% specificity. Many alleged biomarkers were annotated, belonging to the classes of carnitine and glutamine metabolites, C21 steroids, amino acids, acetylcholine, carboxyethyl-hydroxychroman, and dihydro(iso)ferulic acid.

Limited Role of Hair Cortisol and Cortisone Measurement for Detecting Cortisol Autonomy in Patients With Adrenal Incidentalomas

Several studies demonstrated the diagnostic accuracy of hair glucocorticoid measurement in patients with overt Cushing syndrome, but few data are available for patients with adrenal incidentaloma (AI) and cortisol autonomy. The aim of our study was to assess whether measurement of 5 corticosteroid hormones with the ultra-high-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method in the keratin matrix is useful to stratify patients with AI by the presence of autonomous cortisol secretion [ACS] (defined as serum cortisol after 1 mg dexamethasone suppression test (DST) > 138 nmol/l) or possible ACS [PACS] (defined as serum cortisol after 1 mg DST > 50 nmol/l but ≤138 nmol/l). We analysed data of 67 AI patients (32 with cortisol autonomy) and 81 healthy subjects. We did not find any significant statistical difference comparing hair cortisol, cortisone, and 20β-dihydrocortisol concentrations between healthy controls and AI patients, while 6β-hydroxycortisol and 11-deoxycortisol were undetectable. Moreover, no significant difference was found in hair cortisol, cortisone, and 20β-dihydrocortisol levels of AI patients with or without cortisol autonomy. Finally, we did not find any correlation in patients with AI between hormonal concentrations in the keratin matrix and serum, salivary, and urinary cortisol levels, or with body mass index. In conclusion, our findings suggest that hair glucocorticoid measurement is not suitable as a diagnostic test for cortisol autonomy (ACS and PACS).

Accelerated Extraction and Analysis of Ethyl Glucuronide in Hair by Means of Pressurized Liquid Extraction Followed by Liquid Chromatography-Tandem Mass Spectrometry Determination

The measurement of ethyl glucuronide (EtG) in hair is an established practice to evaluate alcohol consumption habits of the donors; nevertheless, analytical variability has shown to be an important factor to be considered: measured EtG values can vary significantly as a consequence of analyte washout during decontamination, pulverization of samples, extraction solvent and incubation temperature. In the present study, we described a new method for automated hair decontamination and EtG extraction from the inner core of the hair by using pressurized liquid extraction (PLE), followed by solid-phase extraction (SPE) cleanup; validation was performed according to SWGTOX guidelines. The extraction efficiency of the new method was evaluated by comparing the results with those obtained by a validated and ISO/IEC 17025:2005 accredited method; an average positive difference of + 32% was observed when the extraction was performed by PLE. The effect of hair pulverization was also studied, and a good correlation between cut and milled hair was observed, implying that PLE allowed a highly efficient extraction of EtG from the inner keratin core of the hair, no matter if it has been cut or pulverized. Finally, to verify the results, paired aliquots of 27 real hair samples were analyzed with both PLE and a protocol optimized by design-of-experiment strategies planned to maximize the extraction yield; in this case, a comparable efficiency was observed, suggesting that exhaustive EtG extraction was obtained with both approaches. This finding opens new perspectives in the eligible protocols devoted to hair EtG analysis, in terms of speed, automation and reproducibility.

The "DOLPHINS" Project: A Low-Cost Real-Time Multivariate Process Control From Large Sensor Arrays Providing Sparse Binary Data

The “DOLPHINS” project started in 2018 under a collaboration between three partners: CNH Industrial Iveco (CHNi), RADA (an informatics company), and the Chemistry Department of the University of Turin. The project’s main aim was to establish a predictive maintenance method in real-time at a pilot plant (CNHi Iveco, Brescia, Italy). This project currently allows maintenance technicians to intervene on machinery preventively, avoiding breakdowns or stops in the production process. For this purpose, several predictive maintenance models were tested starting from databases on programmable logic controllers (PLCs) already available, thus taking advantage of Machine Learning techniques without investing additional resources in purchasing or installing new sensors. The instrumentation and PLCs related to the truck sides’ paneling phase were considered at the beginning of the project. The instrumentation under evaluation was equipped with sensors already connected to PLCs (only on/off switches, i.e., neither analog sensors nor continuous measurements are available, and the data are in sparse binary format) so that the data provided by PLCs were acquired in a binary way before being processed by multivariate data analysis (MDA) models. Several MDA approaches were tested (e.g., PCA, PLS-DA, SVM, XGBoost, and SIMCA) and validated in the plant (in terms of repeated double cross-validation strategies). The optimal approach currently used involves combining PCA and SIMCA models, whose performances are continuously monitored, and the various models are updated and tested weekly. Tuning the time range predictions enabled the shop floor and the maintenance operators to achieve sensitivity and specificity values higher than 90%, but the performance results are constantly improved since new data are collected daily. Furthermore, the information on where to carry out intervention is provided to the maintenance technicians between 30 min and 3 h before the breakdown.

Untargeted Metabolomics in Forensic Toxicology: A New Approach for the Detection of Fentanyl Intake in Urine Samples

The misuse of fentanyl, and novel synthetic opioids (NSO) in general, has become a public health emergency, especially in the United States. The detection of NSO is often challenged by the limited diagnostic time frame allowed by urine sampling and the wide range of chemically modified analogues, continuously introduced to the recreational drug market. In this study, an untargeted metabolomics approach was developed to obtain a comprehensive “fingerprint” of any anomalous and specific metabolic pattern potentially related to fentanyl exposure. In recent years, in vitro models of drug metabolism have emerged as important tools to overcome the limited access to positive urine samples and uncertainties related to the substances actually taken, the possible combined drug intake, and the ingested dose. In this study, an in vivo experiment was designed by incubating HepG2 cell lines with either fentanyl or common drugs of abuse, creating a cohort of 96 samples. These samples, together with 81 urine samples including negative controls and positive samples obtained from recent users of either fentanyl or “traditional” drugs, were subjected to untargeted analysis using both UHPLC reverse phase and HILIC chromatography combined with QTOF mass spectrometry. Data independent acquisition was performed by SWATH in order to obtain a comprehensive profile of the urinary metabolome. After extensive processing, the resulting datasets were initially subjected to unsupervised exploration by principal component analysis (PCA), yielding clear separation of the fentanyl positive samples with respect to both controls and samples positive to other drugs. The urine datasets were then systematically investigated by supervised classification models based on soft independent modeling by class analogy (SIMCA) algorithms, with the end goal of identifying fentanyl users. A final single-class SIMCA model based on an RP dataset and five PCs yielded 96% sensitivity and 74% specificity. The distinguishable metabolic patterns produced by fentanyl in comparison to other opioids opens up new perspectives in the interpretation of the biological activity of fentanyl.

The Impact of COVID-19 Pandemic and Lockdown on Alcohol Consumption: A Perspective From Hair Analysis

Introduction and Aims: The increase in stress levels, social confinement, and addiction's physical consequences play an essential role in the proliferation of drug abuse. In this context, the Covid-19 pandemic produced remarkable effects on those individuals prone to addictions, especially to alcohol. Alcohol is linked to multiple dangerous conditions such as social issues, severe medical conditions, and road accidents. The determination of ethylglucuronide (EtG) in hair is frequently performed to test and monitor chronic excessive alcohol intake conditions, as it allows differentiation among low-risk/moderate drinkers, and excessive/chronic drinkers. Our study aimed to explore hair EtG levels in a controlled population to assess the impact of Covid-19 lockdown on alcohol intake along March-May 2020. Materials and Methods: EtG levels were measured in all hair samples collected in the months following April 2020 to evaluate the behaviors related to alcohol intake along with the time frame from March to May 2020. The measured concentration distributions for each month were compared with those reported in the same month during the previous 4 years (2016-2019). The dataset was built to highlight possible differences between genders, and the different categories of alcohol consumption, separately. Results: The samples collected from April to August 2020 (500 < N <1,100 per month) showed an increase in the percentage of subjects classified as abstinent/low-risk drinkers (from 60 up to 79%) and a decrease of subjects classified as moderate and chronic drinkers (-12 and -7%, respectively) when compared to the previous 4 years. A decrease in the overall mean value of EtG in the period April-June 2020 was observed, while the EtG levels of both June and July 2020 provided an increasing trend for chronic/excessive consumers (+27 and +19% for June and July 2020, respectively). A peculiar rise in the EtG levels of moderate and chronic/excessive female consumers was observed along April-June 2020, too. Discussion and Conclusions: Behavioral and social studies generally report a decrease in alcohol consumption during the Covid-19 lockdown. However, people already suffering from drug or alcohol addictions before Covid-19 pandemic seemingly enhance their harmful behavior. Our data from April to August 2020 are consistent with both suppositions. Our observations confirm once again the utility of EtG to investigate the patterns of alcohol consumption in the population.

Determination of cannabinoids in urine, oral fluid and hair samples after repeated intake of CBD-rich cannabis by smoking

Cannabidiol prevalent (CBD-rich) cannabis derivatives are increasingly popular and widely available on the market as replacement of THC, tobacco substitutes or therapeutics for various health conditions. In this paper, we evaluate the impact of a repeated CBD-rich cannabis intake on levels of cannabinoids in biological samples. Urine, oral fluid and hair (pubic and head) samples were obtained from a naive user during a 26-day smoking period of one 250-mg CBD-rich cannabis joint/day containing 6.0% cannabidiol (CBD; 15mg) and 0.2% delta-9-tetrahydrocannabinol (THC; 0.5mg). In total, 35 urine, 8 oral fluid and 4hair sample were collected. Cannabinoids concentrations were quantified by a UHPLC/MSⁿ technique. The results suggested that the repeated exposure to CBD-rich cannabis (containing small amounts of THC) can generate positive results in biological samples. Urinary concentrations of 11-nor-9-carboxy-delta-9-tetrahydrocannabinol (THC-COOH) were quantitatively detected after 8 days from the smoking start and exceeded the 15ng/mL cut-off limit on day-15 even in the urine sample collected 12h after the last intake. In the oral fluid collected on day-26, no cannabinoids were found before the cannabis intake, thus excluding accumulation, while THC was detectable up to 3h after the cannabis intake, at concentrations progressively decreasing from about 18 to 6ng/mL. Hair samples collected one week after the end of the study turned out negative for THC and THC-COOH, suggesting that this matrix is suitable to discriminate the chronic consumption of CBD-rich cannabis from THC-prevalent products. The obtained findings are relevant for the interpretations of cannabinoids levels in biological fluids, also in light of the legal implications of a positive result.

Evaluation of Forensic Data Using Logistic Regression-Based Classification Methods and an R Shiny Implementation

We demonstrate the use of classification methods that are well-suited for forensic toxicology applications. The methods are based on penalized logistic regression, can be employed when separation occurs in a two-class classification setting, and allow for the calculation of likelihood ratios. A case study of this framework is demonstrated on alcohol biomarker data for classifying chronic alcohol drinkers. The approach can be extended to applications in the fields of analytical and forensic chemistry, where it is a common feature to have a large number of biomarkers, and allows for flexibility in model assumptions such as multivariate normality. While some penalized regression methods have been introduced previously in forensic applications, our study is meant to encourage practitioners to use these powerful methods more widely. As such, based upon our proof-of-concept studies, we also introduce an R Shiny online tool with an intuitive interface able to perform several classification methods. We anticipate that this open-source and free-of-charge application will provide a powerful and dynamic tool to infer the LR value in case of classification tasks.

Targeted and untargeted detection of fentanyl analogues and their metabolites in hair by means of UHPLC-QTOF-HRMS

Detection of new psychoactive substances and synthetic opioids is generally performed by means of targeted methods in mass spectrometry, as they generally provide adequate sensitivity and specificity. Unfortunately, new and unexpected compounds are continuously introduced in the illegal market of abused drugs, preventing timely updating of the analytical procedures. Moreover, the investigation of biological matrices is influenced by metabolism and excretion, in turn affecting the chance of past intake detectability. In this scenario, new opportunities are offered by both the non-targeted approaches allowed by modern UHPLC-HRMS instrumentation and the investigation of hair as the matrix of choice to detect long-term exposure to toxicologically relevant substances. In this study, we present a comprehensive and validated workflow that combines the use of UHPLC-QTOF-HRMS instrumentation with a simple hair sample extraction procedure for the detection of a variety of fentanyl analogues and metabolites. A simultaneous targeted and untargeted analysis was applied to 100 real samples taken from opiates users. MS and MS/MS data were collected for each sample. Data acquisition included a TOF-MS high-resolution scan combined with TOF-MS/MS acquisition demonstrating considerable capability to detect expected and unexpected substances even at low concentration levels. The predominant diffusion of fentanyl was confirmed by its detection in 68 hair samples. Other prevalent analogues were furanylfentanyl (28 positive samples) and acetylfentanyl (14 positive samples). Carfentanil, methylfentanyl, and ocfentanil were not found in any of the analyzed samples. Furthermore, the retrospective data analysis based on untargeted acquisition allowed the identification of two fentanyl analogues, namely β-hydroxyfentanyl and methoxyacetylfentanyl, which were not originally included in the panel of targeted analytes.

Toward the Interpretation of Positive Testing for Fentanyl and Its Analogs in Real Hair Samples: Preliminary Considerations

The detection of new psychoactive substances (NPS) in hair has become extensively researched in recent years. Although most NPS fall into the classes of synthetic cannabinoids and designer cathinones, novel synthetic opioids (NSO) have appeared with increasing frequency in the illicit drug supply. While the detection of NSO in hair is now well documented, interpretation of results presents several controversial issues, as is quite common in hair analysis. In this study, an ultra-high-performance liquid chromatography-tandem mass spectrometry method able to detect 13 synthetic opioids (including fentanyl analogs) and metabolites in hair was applied to 293 real samples. Samples were collected in the USA between November 2016 and August 2018 from subjects who had reported heroin use in the past year or had already tested positive to hair testing for common opiates. The range, mean and median concentrations were calculated for each analyte, in order to draw a preliminary direction for a possible cut-off to discriminate between exposure to either low or high quantities of the drug. Over two-thirds (68%) of samples tested positive for fentanyl at concentrations between LOQ and 8600 pg/mg. The mean value was 382 pg/mg and the median was 95 pg/mg. The metabolites norfentanyl and 4-ANPP were also quantified and were found between LOQ and 320 pg/mg and between LOQ and 1400 pg/mg, respectively. The concentration ratios norfentanyl/fentanyl, 4-ANPP/fentanyl and norfentanyl/4-ANPP were also tested as potential markers of active use and to discriminate the intake of fentanyl from other analogs. The common occurrence of samples positive for multiple drugs may suggest that use is equally prevalent among consumers, which is not the case, as correlations based on quantitative results demonstrated. We believe this set of experimental observations provides a useful starting point for a wide discussion aimed to better understand positive hair testing for fentanyl and its analogs in hair samples.

Optimization and validation of a GC-MS quantitative method for the determination of an extended estrogenic profile in human urine: Variability intervals in a population of healthy women

An analytical method based on GC-MS was developed for the determination of a wide panel of urinary estrogens, together with their principal metabolites. Because of the low concentration of estrogens in urine, an efficient sample pre-treatment was optimized by a design of experiment (DoE) procedure to achieve satisfactory sensitivity. A second DoE was built for the optimization of the chromatographic run, with the purpose of reaching the most efficient separation of analytes with potentially interfering ions and similar chromatographic properties. The method was fully validated using a rigorous calibration strategy: from several replicate analyses of blank urine samples spiked with the analytes, calibration models were built with particular attention to the study of heteroscedasticity and quadraticity. Other validation parameters, including the limit of detection, intra-assay precision and accuracy, repeatability, selectivity, specificity, and carry-over, were obtained using the same set of data. Further experiments were performed to evaluate matrix effect and extraction recovery. Then the urinary estrogen profiles of 138 post-menopausal healthy women were determined. These profiles provide a representation of physiological concentration ranges, which, in forthcoming studies, will be matched on the base of multivariate statistics with the urinary estrogenic profile of women with breast or ovarian cancer.

Experimental and statistical protocol for the effective validation of chromatographic analytical methods

The validation of analytical methods is of crucial importance in several fields of application. A new protocol for the validation of chromatographic methods has been proposed. The overall protocol is described in a parallel paper, where the case of a multi-targeted gas chromatography – mass spectrometry (GC–MS) method for the determination of androgens in human urine is in-depth discussed. The purpose of this paper is to report the details about the GC–MS separation and detection of the target analytes, and to provide the mathematical formulas needed to perform the validation of the principal parameters. Briefly, the validation protocol foresees the repetition of three calibration curves in three different days, providing a total amount of nine replicates. Such a structured design allows to use the same experiments to•

perform a rigorous calibration study, by the evaluation of heteroscedasticity, comparison of several weights and linear/quadratic calibration curves.

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determine several parameters which are traditionally computed from dedicated experiments, namely intra- and inter-day accuracy and precision, limit of detection, specificity, selectivity, ion abundance repeatability, and carry over.

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Finally, few further experiments are necessary to evaluate the retention time repeatability, matrix effect and extraction recovery.

Prospective evaluation of urinary steroids and prostate carcinoma-induced deviation: preliminary results

BACKGROUND

The serum prostate-specific antigen is the most widespread biomarker for prostate disease. Its low specificity for prostatic malignancies is a matter of concern and the reason why new biomarkers for screening purposes are needed. The correlation between altered production of the main steroids and prostate carcinoma (PCa) occurrence is historically known. The purpose of this study is to evaluate the modifications of a comprehensive urinary endogenous steroidal profile (USP) induced by PCa, by multivariate statistical methods.

METHODS

A total of 283 Italian subjects were included in the study, 139 controls and 144 PCa-affected patients. The USP, including 17 steroids and five urinary steroidal ratios, was quantitatively evaluated using gas chromatography coupled with single quadrupole mass spectrometry (GC-MS). The data were interpreted using a chemometric, multivariate approach (intrinsically more sensible to alterations with respect to traditional statistics) and a model for the discrimination of cancer-affected profiles was built.

RESULTS

Two multivariate classification models were calculated, the former including three steroids with the highest statistical significance (e.g. testosterone, etiocholanolone and 7β-OH-DHEA) and PSA values, the latter considering the three steroids' levels only. Both models yielded high sensitivity and specificity scores near to 70%, resulting significantly higher than PSA alone.

CONCLUSIONS

Three USP steroids resulted significantly altered in our PCa population. These preliminary results, combined with the simplicity and low-cost of the analysis, open to further investigation of the potential role of this restricted USP in PCa diagnosis.

A multivariate statistical approach for the estimation of the ethnic origin of unknown genetic profiles in forensic genetics

DNA typing and genetic profile data interpretation are among the most relevant topics in forensic science; among other applications, genetic profile's capability to distinguish biogeographic information about population groups, subgroups and affiliations have been largely explored in the last decade. In fact, for investigative and intelligence purposes, it is extremely useful to identify subjects and estimate their biogeographic origins by examining the recovered DNA profiles from evidence on a crime scene. Current approaches for BiogeoGraphic Ancestry (BGA) estimation using STRs profiles are usually based on Bayesian methods, which quantify the evidence in terms of likelihood ratio, supporting or not the hypothesis that a certain profile belongs to a specific ethnic group. The present study provides an alternative approach to the likelihood ratio method that involves multivariate data analysis strategies for the estimation of multiple populations. Starting from the well-known NIST US autosomal STRs dataset involving African-American, Asian, and Caucasian individuals, and moving towards further and more geographically restricted populations (such as Northern Africans vs sub-Saharan Africans, Afghans vs Iraqis and Italians vs Romanians), powerful multivariate techniques such as Sparse and Logistic Principal Component Analysis (SL-PCA), Sparse Partial Least Squares-Discriminant Analysis (sPLS-DA) and Support Vector Machines (SVM) were employed and their discriminating power was also compared. Both sPLS-DA and SVM techniques provided robust classifications, yielding high sensitivity and specificity models capable of discriminating populations on ethnic basis. This application may represent a powerful and dynamic tool for law enforcement agencies whenever a standard autosomal STR profile is obtained from the biological evidence collected at a crime scene or recovered during mass-disaster and missing person investigations.

Individual and cyclic estrogenic profile in women: Structure and variability of the data

The concentration of estrogens in the body fluids of women is highly variable, due to the menstrual cycle, circadian oscillations, and other physiological and pathological causes. To date, only the cyclic fluctuations of the principal estrogens (estradiol and estrone) have been studied, with limited outcome of general significance. Aim of the present study was to examine in detail the cyclic variability of a wide estrogens' panel and to interpret it by multivariate statistics. Four estrogens (17α-estradiol, 17β-estradiol, estrone, estriol) and eleven of their metabolites (4-methoxyestrone, 2-methoxyestrone, 16α-hydroxyestrone, 4-hydroxyestrone, 2-hydroxyestrone, 4-methoxyestradiol, 2-methoxyestradiol, 4-hydroxyestradiol, 2-hydroxyestradiol, estriol, 16-epiestriol, and 17-epiestriol) were determined in urine by a gas chromatography - mass spectrometry method, which was developed by design of experiments and fully validated according to ISO 17025 requirements. Then, urine samples collected every morning for a complete menstrual cycle from 9 female volunteers aged 24-35 years (1 parous) were analysed. The resulting three-dimensional data (subjects × days × estrogens) were interpreted using several statistical tools. Parallel Factor Analysis compared the estrogen profiles in order to explore the cyclic and inter-individual variability of each analyte. Principal Component Analysis (PCA) provided clear separation of the sampling days along the cycle, allowing discrimination among the luteal, ovulation, and follicular phases. The scores obtained from PCA were used to build a Linear Discriminant Analysis classification model which enhanced the recognition of the three cycle's phases, yielding an overall classification non-error rate equal to 90%. These statistical models may find prospective application in fertility studies and the investigation of endocrinology disorders and other hormone-dependent diseases.

Effects of truck transportation and slaughtering on the occurrence of prednisolone and its metabolites in cow urine, liver, and adrenal glands

Background

The recognition of illegal administration of synthetic corticosteroids in animal husbandry has been recently challenged by the case of prednisolone, whose occasional presence in the urine of bovines under strong stressful conditions was attributed to endogenous biosynthesis, not to exogenous administration. The study of the natural stress sources possibly inducing endogenous prednisolone production represents a stimulating investigation subject. The biochemical effects of transportation and slaughtering were verified in untreated cows by studying the possible occurrence of prednisolone and its metabolites in urine, liver and adrenal glands, and the cortisol/cortisone quantification.

Results

Cortisol, cortisone, prednisolone and its metabolites were measured in urine, collected at farm under natural micturition and then at the slaughterhouse. The study was performed on 15 untreated cows reared in different farms at the end of their productive cycle. 2–3 days after the first urine collection, the animals were transported by trucks to the abattoir, slaughtered, and subjected to a second urine sampling from the bladder. Specimens of liver and adrenal gland were also collected and analysed by means of a liquid chromatography-tandem mass spectrometry (LC-MS/MS) validated method. The stressful conditions of transportation and slaughtering proved to increase considerably the urinary levels of cortisol and cortisone as compared to those collected at farm. Prednisolone was detected in the urine collected at the slaughterhouse of two cows only, at a concentration level (≈0.6 μg L^− 1) largely below the official cut off (5.0 μg L^− 1) established to avoid false non-compliances. These two animals exhibited the highest urinary cortisol levels of the series. Prednisolone and prednisone were also detected in the adrenal glands of a different cow. Prednisolone metabolites were not detected in any urine, liver, and adrenal gland sample.

Conclusion

Within the constraints of the condition adopted, this study confirms the sporadic presence of prednisolone traces (2 samples out of 15) and the consistently increased concentration of cortisone and cortisol in the urines collected from cows subjected to truck transportation and subsequent slaughtering. No prednisolone metabolites were detected in any liver and adrenal gland samples, nor in urine specimens, unlike what was previously reported for cows artificially stressed by pharmacological treatment.

Multivariate interpretation of the urinary steroid profile and training-induced modifications. The case study of a Marathon runner

The steroidal module of the athlete biological passport (ABP) introduced by the World Anti-Doping Agency (WADA) in 2014 includes six endogenous androgenic steroids and five of their concentration ratios, monitored in urine samples collected repeatedly from the same athlete, whose values are interpreted by a Bayesian model on the basis of intra-individual variability. The same steroid profile, plus dihydrotestosterone (DHT) and DHEA, was determined in 198 urine samples collected from an amateur marathon runner monitored over three months preceding an international competition. Two to three samples were collected each day and subsequently analyzed by a fully validated gas chromatography-mass spectrometry protocol. The objective of the study was to identify the potential effects of physical activity at different intensity levels on the physiological steroid profile of the athlete. The results were interpreted using principal component analysis and Hotelling's T² vs Q residuals plots, and were compared with a profile model based on the samples collected after rest. The urine samples collected after activity of moderate or high intensity, in terms of cardiac frequency and/or distance run, proved to modify the basal steroid profile, with particular enhancement of testosterone, epitestosterone, and 5α-androstane-3α,17β-diol. In contrast, all steroid concentration ratios were apparently not modified by intense exercise. The alteration of steroid profiles seemingly lasted for few hours, as most of the samples collected 6 or more hours after training showed profiles compatible with the "after rest" model. These observations issue a warning about the ABP results obtained immediately post-competition.

Furosemide as a functional marker of acute kidney injury in ICU patients: a new role for an old drug

New pharmacokinetics insight suggests that the furosemide pharmacology occurring in ICU patients with AKI is similar, but not equal to that described in chronic stable renal patients. Even if the diuretic response to furosemide is expressed by a steep dose-response curve positively correlated with renal function, pharmacodynamic limitations occur when creatinine clearance is < 20 ml/min or urine output is < 500 ml/12 h. In such cases, other factors specifically due to acute tubular injury can interfere with the furosemide-induced diuretic output. As modality of administration recent reports and metanalysis, even if not conclusive, suggest that for the same given dose a continuous infusion of furosemide was superior in diuretic response. For septic shock patients on CVVHDF where treatment adds an additional clearance of furosemide the maximum diuretic response is achieved by a continuous infusion of 20 mg/h of furosemide. At this infusion rate the reached plasma level was < 20 mg/L, a range considered safe and not ototoxic. Therefore, the severity of AKI establishes whether a patient will respond to furosemide. In this review we summarized all these recent updates, also suggesting that the diuretic response under continuous infusion may allow assessing glomerular and tubular functions with increased reliability than a bolus dose. However, validation studies are still needed to support continuous infusion as a stress test.

Detection of Fentanyl Analogs and Synthetic Opioids in Real Hair Samples

Novel synthetic opioids include various analogs of fentanyl and emerging non-fentanyl compounds with different chemical structures, such as AH-7921, MT-45 and U-47700. In recent years, these drugs have rapidly emerged on the drug market, and their abuse has been increasing worldwide. The motivations for use of these new compounds include their legal status, ready availability, low cost, users' curiosity or preference for their particular pharmacological properties and the intention to avoid detection. Furthermore, more common drugs like heroin are now increasingly being replaced or cut with fentanyl or new designer opioids; thus, many drug users are unintentionally or unknowingly using synthetic fentanyl analogs. In this scenario, the detection of new psychoactive substances in hair can provide insight into their current diffusion among the population and social characteristics of these synthetic drug users. In this manuscript, we describe a simple, fast, specific and sensitive UHPLC-MS-MS method able to detect 13 synthetic opioids (including fentanyl analogs) and metabolites in hair samples. Furthermore, the method includes the detection of 4-anilino-N-phenethyl-piperidine (4-ANPP), which is considered both a precursor and a metabolite of several fentanyl analogs. The method was applied to 34 real hair samples collected in New York City from subjects who had reported past-year non-medical opioid and/or heroin use. In total, 17 samples tested positive for at least one target analyte, with oxycodone (nine samples) and tramadol (eight samples) being the most common. Among these, the method was able to quantify furanyl-fentanyl and fentanyl in the pg/mg range in two samples. Simultaneously, also 4-ANPP was detected, giving evidence for the first time that this compound can be selected as a marker of fentanyl analogs use via hair testing. In conclusion, this study confirmed the increasing diffusion of new synthetic opioids and "fentalogs" with high potency among non-medical opioid users.

On-site identification of psychoactive drugs by portable Raman spectroscopy during drug-checking service in electronic music events

INTRODUCTION AND AIMS

Hundreds of new psychoactive substances (NPS) have burst into the marketplace, making both the scientific community and people who use drugs lacking of adequate information about their diffusion and effects. In this scenario, drug-checking services have been recently proposed to assist harm reduction policies and provide a global description of the circulating drugs.

DESIGN AND METHODS

The results obtained by a portable Raman spectroscopy device on 472 alleged drugs within the first formal implementation of drug checking in Italy, are reported. The testing was made through a plastic bag held by the applicant and containing the alleged drug. The substance identification was executed by comparison with a spectral library.

RESULTS

Illicit substances were detected in 304 samples. Findings included MDMA (106 samples), ketamine (87 samples), cocaine (51 samples), amphetamine (47 samples), methamphetamine (two samples), heroin (two samples) and NPS (nine samples). Two samples were identified as precursors of psychoactive substances. Identification of a non-controlled substance occurred in 38 samples. Output of inconclusive result was recorded from 128 samples tested on-site, from which the applicant allowed us to collect a small portion in 68 cases, for a delayed laboratory analysis by GC-MS or LC-MS/MS.

DISCUSSION AND CONCLUSIONS

Drug checking by Raman spectroscopy proved effective to identify psychoactive drugs including NPS and track the drug distribution in various recreational settings. The field testing activity revealed the presence of several NPS in the nightlife scenario, often in replacement of traditional illicit drugs, thus posing a high overdose risk and a life-threatening situation.